CN110927585A - Lithium battery SOH estimation system and method based on self-circulation correction - Google Patents

Lithium battery SOH estimation system and method based on self-circulation correction Download PDF

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CN110927585A
CN110927585A CN201911410907.4A CN201911410907A CN110927585A CN 110927585 A CN110927585 A CN 110927585A CN 201911410907 A CN201911410907 A CN 201911410907A CN 110927585 A CN110927585 A CN 110927585A
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soh
self
lithium battery
battery
circulation
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孟令锋
周迅
黄勇
廖红
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Sichuan Changhong Electric Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC

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Abstract

The invention relates to the technical field of battery management, and discloses a lithium battery SOH estimation system and method based on self-circulation correction. The system comprises: the data acquisition module is used for acquiring the operation data of the lithium battery system; the SOH estimation module is used for estimating the SOH by utilizing the operation data of the lithium battery system; and the self-circulation correction module is used for comparing errors between the SOH estimated value and the pre-acquired battery circulation charge-discharge experimental data of the same batch through self-circulation charge-discharge data analysis and correcting the SOH of the battery.

Description

Lithium battery SOH estimation system and method based on self-circulation correction
Technical Field
The invention relates to the technical field of battery management, in particular to a lithium battery SOH estimation system and method based on self-circulation correction.
Background
In recent years, with the increasing severity of energy problems and environmental pollution problems, energy conservation, emission reduction and the search for alternative fuels become more and more concerned in various countries. The new energy technology plays an increasingly important role in the energy industry and the automobile industry due to the characteristics of energy conservation, environmental protection and recycling.
Since the 20 th century and the 70 th era, lithium ion batteries, as important energy storage devices, have been the key content of new energy technology research due to the characteristics of high energy density, low self-discharge rate and strong stability. The state of health (SOH) of a battery is the ratio of the current charge capacity to the nominal capacity of the battery, and represents the active electrochemical substance of the battery, which is an important standard for measuring the performance of the battery. The existing SOH measurement mainly adopts a complete charge-discharge method, and is characterized in that although the measurement result is accurate, on one hand, the complete charge-discharge requires long waiting time and is not suitable for practical application scenes, and on the other hand, the complete charge-discharge has certain damage to a battery. In the prior art, there is also a scheme of modeling a battery and then predicting SOH of a model, for example, the "SOC/SOH prediction method for a power battery based on a big data self-learning mechanism" proposed by CN201510532492.3 adopts a modeling method and then performs SOH prediction, but on one hand, battery modeling has high time cost and low practicability, and meanwhile, a prediction algorithm adopted by the method cannot ensure data convergence, which may cause divergence of a prediction result.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the system and the method for estimating the SOH of the lithium battery based on self-circulation correction are provided, and the accuracy of estimating the SOH of the lithium battery is improved and the reliability of a battery management system is improved on the premise of ensuring the convergence of a prediction result by self-circulation correction of the estimated value of the SOH.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a lithium battery SOH estimation system based on self-circulation correction comprises:
the data acquisition module is used for acquiring the operation data of the lithium battery system;
the SOH estimation module is used for estimating the SOH by utilizing the operation data of the lithium battery system;
and the self-circulation correction module is used for comparing errors between the SOH estimated value and the pre-acquired battery circulation charge-discharge experimental data of the same batch through self-circulation charge-discharge data analysis and correcting the SOH of the battery.
In addition, based on the system, the invention also provides a corresponding lithium battery SOH estimation method based on self-circulation correction, which comprises the following steps:
a. collecting operation data of the lithium battery system;
b. estimating SOH by utilizing the operation data of the lithium battery system;
c. and through self-circulation charging and discharging data analysis, comparing errors between the estimated SOH value and the pre-obtained circulation charging and discharging experimental data of the batteries in the same batch, and correcting the SOH of the batteries.
As a further optimization, in step a, the operation data comprises current, voltage, temperature, operation time and cycle charge and discharge number data of the battery.
And b, as a further optimization, estimating the SOH value of the battery by using a Kalman filtering method, an internal resistance method or an electrochemical impedance method based on the operation data of the lithium battery system.
As a further optimization, in step c, the method for obtaining the cycle charge and discharge experimental data of the batteries in the same batch in advance comprises the following steps:
firstly, selecting a plurality of lithium batteries of the same material, the same specification and the same batch to perform a cyclic charge-discharge test, and recording the cycle times and the full charge capacity;
then, averaging the recorded data of the plurality of lithium batteries according to the cycle times, and dividing the average value of the full charge capacity corresponding to the cycle times by the nominal capacity to obtain the SOH value corresponding to the cycle times, thereby establishing a corresponding relation table of the cycle times and the SOH.
As a further optimization, in step c, comparing the error between the SOH estimate and the pre-obtained experimental data of the battery cycle charge and discharge in the same batch, the correcting the SOH of the battery specifically includes:
and inquiring a corresponding relation table of the cycle times and the SOH according to the current cycle times of the battery to obtain a table-lookup SOH value, comparing the SOH estimated value with the table-lookup SOH value, and if the error is more than 5%, correcting the estimated value by taking the table-lookup SOH as a reference.
The invention has the beneficial effects that:
the estimated SOH value is corrected through the comparison error between the current self-circulation data of the lithium battery to be corrected and the pre-acquired historical circulation charge-discharge experimental data of the batteries in the same batch, so that the calculation accuracy of the SOH of the lithium battery is improved on the premise of ensuring the convergence of the prediction result, and the reliability of a battery management system is improved.
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FIG. 1 is a block diagram of a self-loop correction based SOH estimation system for lithium batteries according to the present invention.
Detailed Description
The invention aims to provide a lithium battery SOH estimation system and method based on self-circulation correction, which improve the accuracy of lithium battery SOH estimation and the reliability of a battery management system on the premise of ensuring the convergence of a prediction result by self-circulation correction of an SOH estimation value.
As shown in fig. 1, the lithium battery SOH estimation system based on self-circulation correction in the present invention includes a data acquisition module, an SOH value estimation module, and a self-circulation correction module, which specifically includes:
(1) and the data acquisition module is responsible for acquiring data such as current, voltage, temperature, operation time, cycle frequency and the like of the operation of the battery and is used as a basis for estimating the SOH value of the lithium battery.
(2) The SOH value estimation module is responsible for estimating the SOH value of the current lithium battery according to the collected lithium battery operation data, and takes the estimation of the SOH value by using a kalman filter algorithm as an example, which is described as follows:
① since the internal resistance of the lithium battery will increase with the increase of the using time in the using process, although the change of the internal resistance of the battery is a slow changing process, it has obvious corresponding relation with the SOH value of the battery, so the internal resistance value of the battery can be calculated by using Kalman filtering algorithm, thereby estimating the SOH value.
② the standard formula of the extended Kalman filter calculation is:
xk+1＝Akxk+Bkuk+Wk(1)
yk＝Ckxx+vk(2)
wherein A iskIs a system matrix, BkTo control the input matrix, WkAs system noise, CkTo measure the matrix, vkFor measuring noise, k is the system time, xk+1System state at time k +1, ykIs the output of the system at the moment k.
Let PkIs xkCorresponding covariance matrix, KkFor the kalman filter gain at time k, the above two equations (1) and (2) can be derived as the following two sets of equations:
1) time update system of equations:
xk+1＝Axk+Buk(3)
Pk+1＝APkAT+Q (4)
wherein Q is the system noise WkThe covariance matrix of (2).
2) Measurement update equation set:
Figure BDA0002349934810000031
xk+1＝xk+Kk(yk-xk) (6)
Pk+1＝(1-Kk)Pk(7)
wherein R is the measurement noise vkThe covariance matrix of (2).
③ according to the time update equation set and the measurement update equation set in ②, the system measurement current, voltage and time are brought into the formulas (3) to (7), and the battery state of charge (SOC) value can be obtained iteratively.
④, establishing an equivalent equation of battery internal resistance estimation and SOH estimation according to the second-order RC equivalent circuit model of the lithium battery and the definition of SOH:
Figure BDA0002349934810000041
R0,k+1＝R0,k+rk(9)
Uk＝V(SOCk)-U1,k-R0,kIk(10)
in the formula, RnewIs the nominal internal resistance, R, of the battery0Is the current internal resistance of the battery, rkFor process noise at time k, UkMeasuring the voltage, V (SOC) for time kk) Is a voltage value corresponding to the current SOC, U1,kIs a voltage disturbance.
The current SOH value of the battery can be calculated through the steps (8) to (10) in combination with the calculated value of the SOC of the battery.
(3) The self-circulation correction module is used for correcting the estimated SOH value of the Kalman filtering according to the battery self-circulation and the battery circulation test data of the same batch:
① A plurality of lithium batteries with the same material, the same specification and the same batch are selected for cycle test, and the cycle times and the full charge capacity are recorded.
②, averaging the recorded data according to the cycle times and making a table, and further obtaining the corresponding relation between the cycle times and the SOH, for example, taking eight batteries to perform a cycle test, obtaining the average value of the full charge capacity of the lithium battery after the first cycle from the cycle record, dividing the full charge capacity by the nominal capacity to obtain the SOH value in the current cycle times, and so on, obtaining a capacity average value table after each cycle and a corresponding relation table between the cycle times and the SOH.
③ after calculation of the SOH estimation module, according to battery cycle times table lookup, subtracting the SOH value of table lookup from the estimated SOH value, if the error between the two is more than 5%, correcting the estimated value by taking the SOH of table lookup as the standard, and correcting the iteration value of Kalman filtering calculation, thereby enabling the calculation of the SOH value to be more accurate.

Claims (6)

1. A lithium battery SOH estimation system based on self-circulation correction is characterized by comprising:
the data acquisition module is used for acquiring the operation data of the lithium battery system;
the SOH estimation module is used for estimating the SOH by utilizing the operation data of the lithium battery system;
and the self-circulation correction module is used for comparing errors between the SOH estimated value and the pre-acquired battery circulation charge-discharge experimental data of the same batch through self-circulation charge-discharge data analysis and correcting the SOH of the battery.
2. A lithium battery SOH estimation method based on self-circulation correction is characterized by comprising the following steps:
a. collecting operation data of the lithium battery system;
b. estimating SOH by utilizing the operation data of the lithium battery system;
c. and through self-circulation charging and discharging data analysis, comparing errors between the estimated SOH value and the pre-obtained circulation charging and discharging experimental data of the batteries in the same batch, and correcting the SOH of the batteries.
3. The lithium battery SOH estimation method based on self-circulation correction as claimed in claim 2, wherein,
in the step a, the operation data comprises current, voltage, temperature, operation time and cycle charge and discharge times of the battery.
4. The lithium battery SOH estimation method based on self-circulation correction as claimed in claim 2, wherein,
and in the step b, estimating by using a Kalman filtering method, an internal resistance method or an electrochemical impedance method based on the operation data of the lithium battery system to obtain the SOH value of the battery.
5. The lithium battery SOH estimation method based on self-circulation correction as claimed in claim 2, wherein,
in step c, the method for obtaining the cyclic charge and discharge experimental data of the batteries in the same batch in advance comprises the following steps:
firstly, selecting a plurality of lithium batteries of the same material, the same specification and the same batch to perform a cyclic charge-discharge test, and recording the cycle times and the full charge capacity;
then, averaging the recorded data of the plurality of lithium batteries according to the cycle times, and dividing the average value of the full charge capacity corresponding to the cycle times by the nominal capacity to obtain the SOH value corresponding to the cycle times, thereby establishing a corresponding relation table of the cycle times and the SOH.
6. The lithium battery SOH estimation method based on self-circulation correction according to claim 5, wherein,
in step c, comparing the error between the SOH estimation value and the pre-obtained experimental data of the battery cycle charge and discharge in the same batch, and correcting the SOH of the battery specifically comprises:
and inquiring a corresponding relation table of the cycle times and the SOH according to the current cycle times of the battery to obtain a table-lookup SOH value, comparing the SOH estimated value with the table-lookup SOH value, and if the error is more than 5%, correcting the estimated value by taking the table-lookup SOH as a reference.
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CN113408138A (en) * 2021-06-29 2021-09-17 广东工业大学 Lithium battery SOH estimation method and system based on secondary fusion

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